• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.336-344
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• 2005

In this paper, we extracted the contour of lung parenchyma on EBT images with the improved active contour model. The objects boundary in conventional active contour model can be extracted by controlling internal energy and external energy as energy minimizing form. However, there are a number of problems such as initialization and the poor convergence about concave part. Expecially, contour can not enter the concave region by discouraging characteristic about stretching and bending in internal energy. We controlled internal energy by moving local perpendicular bisector point of each control point in the contour and implemented the object boundary by minimizing energy with external energy The convergence of concave part could be efficiently implemented toward lung parenchyma region by this internal energy and both lung images for initial contour could also be detected by multi-detection method. We were sure this method could be applied detection of lung parenchyma region in medical image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.465-468
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• 2005

MMA(Multi-Modulus Algorithm) is inferior at a initial equalization in high ISI(intersymbol interference), because it is the inaccurate decision. To improve this probel SMMA(Sliced Multi-Modulus Algorithm) is based on using the MCMA(Modified Constant Modulus Algorithm). SMMA is a improved capability than MMA in high SNR but is inaccurate decision in low SNR. In this paper, We propose some multi-modulus blind equalization algorithm scheme. It is a method of operation in some multi-modulus algorithm which does no obstruct a convergence property at the initial equalization in the low SNR. Proposed algorithm improves the steady-state performance. And it uses residual ISI of the equalizer output in order to decide the optimum switching time between the single modulus and the multi-modulus algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.477-480
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• 2005

CMA-DD is proposed to improve the steady-state performance of CMA and its performance is depending on switching time between two modes of operation. Castro et al. who proposed a concurrent equalizer for solving problem of CMA-DD, which reduced the sensibility of switching time. However, concurrent algorithm has a problem that it keeps working after convergence. In this paper, we propose concurrent MCMA-DD equalizer combined modified CMA(MCMA) and DD mode for making better concurrent algorithm. The proposed equalizer is better than previous algorithm in convergence speed and steady-state performance. Also, the proposed algorithm decides optimum switching time using residual ISI of the equalizer output.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.4
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• pp.83-92
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• 1999

본 논문에서는 Jue Chang 과 John R. Glover 가 1993년에 제안한 회귀적 적응 주기 신호 검출기[1]를 소개하고 이를 구현하기 위한 최적의 실시간 알고리즘을 제안하여 회귀적 주기 신호 검출기의 실용적인 응용 예를 제시하였다. 회귀적 적응 주기신호 검출기(FALE:Feedback Adaptive Line Enhancer)는 기존의 적응 주기 신호 검출기에 회귀 경로를 달아줌으로써, 필터 차수를 같게 했을 때 낮은 신호 대 잡음비 환경 하에서 더 높은 필터 이득과 더 낮은 추정 오차를 얻을 수 있다. 회귀 경로를 통해 들어오는 필터 출력 신호는 회귀 이득 상수 값에 따라 전체 시스템의 성능이 달라지므로 최적의 회귀 이득 상수를 찾아내는 것이 중요하며 이는 회귀 이득 상수를 변화시키며 최적의 결과값(최소 추정오차)을 유도하는 실험을 통해 얻을 수 있다. 한편, 이를 구현하는 문제에 있어서는 일잔 최적의 회귀 이득 상수 값이 정해지면 회귀 이득 상수가 초기 값으로부터 최적 값에 도달하는 변화율과 변화 유형이 시스템의 실시간 구현 및 성능에 중요한 영향을 미치게 된다. 본 논문에서는 실험을 통해 최적의 구현 알고리즘을 찾아냄으로써 Jue Chang 과 John R, Glover가 제시한 이론적인 수렴율과 수렴 성능을 유지하면서 실시간으로 동작하는 시스템을 구현하고 모의실험을 통한 성능분석 결과를 제시하였다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.8
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• pp.81-87
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• 1999

In general, feature detection and tracking algorithms is classified by EBGM using Garbor-jet, NNC-R and STK algorithm using pixel eigenvalue. In those algorithms, EBGM and NCC-R detect features with feature model, but STK algorithm has a characteristics of an automatic feature selection. In this paper, to solve the initial problem of NR tracking in STK algorithm, we detected features using STK algorithm in modelled feature region and tracked features with NR method. In tracking, to improve the tracking accuracy for features by NR method, we proposed BMA-NR method. We evaluated that BMA-NR method was superior to NBMA-NR in that feature tracking accuracy, since BMA-NR method was able to solve the local minimum problem due to search window size of NR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1972-1978
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• 2010

AAM(Active Appearance Model) is one of the most effective ways to detect deformable 2D objects and is a kind of mathematical optimization methods. The cost function is a convex function because it is a least-square function, but the search space is not convex space so it is not guaranteed that a local minimum is the optimal solution. That is, if the initial value does not depart from around the global minimum, it converges to a local minimum, so it is difficult to detect face contour correctly. In this study, an AAM-based face tracking algorithm is proposed, which is robust to various lighting conditions and backgrounds. Eye detection is performed using SIFT and Genetic algorithm, the information of eye are used for AAM's initial matching information. Through experiments, it is verified that the proposed AAM-based face tracking method is more robust with respect to pose and background of face than the conventional basic AAM-based face tracking method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.478-486
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• 2007

Double-talk detection errors can result in either large residual echo or distorting the near-end talker's input speech. Thus accurate double-talk detection is an important problem in the acoustic echo canceller to improve the speech quality. In the double-talk detection algorithm using a cross-correlation coefficient, double-talk detection errors can occur in the initial convergence period of an adaptive filter or in noisy environment since the cross-correlation coefficient becomes large in such situations. In this paper, we propose a new double-talk detection algorithm based on the cross-correlation method using a normalized error signal power to reduce the double-talk detection errors. The experimental results have shown the performance improvement of an acoustic echo canceller as well as the noise-robustness of the proposed double-talk detector.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.445-447
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• 2005

MCMA(modified constant modulus algorithm) accomplishes blind equalization and carrier phase recovery simultaneously. But, the error level of MCMA is not zero when the equalizer converges completely. Because the MCMA uses a special signal point instead of a original signal point. MCMA-DO(decision-directed) improves the steady-state performance but the performance of equalizer is decided by switching time between the MCMA and the DD. In this paper, according to the residual ISI(intersymbol interference) of the equalizer output, the most suitable switching time is decided automatically.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.183-194
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• 2009

In this paper, we propose a new method for detecting objectionable images with an active shape model. Our method first learns the shape of breast lines through principle component analysis and alignment as well as the distribution of intensity values of corresponding landmarks, and then extracts breast lines with the learned shape and intensity distribution. To accurately select the initial position of active shape model, we obtain parameters on scale, rotation, and translation. After positioning the initial location of active shape model using scale and rotation information, iterative searches are performed. We can identify adult images by calculating the average of the distance between each landmark and a candidate breast line. The experiment results show that the proposed method can detect adult images effectively by comparing various results.